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A process with no memory (no aftereffects, Markovian) on a large time interval may well have a local memory on small intervals.
Then it should still be called a process with memory. Unfortunately, this is the accepted terminology, although I don't like it either.
For processes with "partial" memory there seems to be simply no terms, because academic science has not yet grasped such phenomena) By the way, exactly for this reason all "Nobel laureates", etc. -physicists-mathematicians and can't earn anything :)Here is the code. This is the one from Alexander's second graph.
The sum of returnees for N is just Open[i] - Open[i+N] :)
The sum of returnees for N is simply Open[i] - Open[i+N] :)
Where is the sum here?
Don't pick on me, I forgot to put the big sigma with the summation limits.
Where is the sum here?
In your code:
In your code:
So what's wrong? I don't get it.
So what's wrong? I don't get it.
It's true, it's just that the algorithm doesn't make sense. Instead of summing up the set of increments, you can just take the difference between the two extreme points. The use of meaningless algorithms (by Alexander the Second) indicates a lack of understanding of the essence of what he works with) And you use his meaningless black boxes in the dark and waste your precious time on nothing)
It's true, it's just that the algorithm doesn't make sense. Instead of summing up the set of increments, you can simply take the difference between the two extreme points.
What so ?
The formula has already been written here many times.
Here is the code. This is what's on the second chart from Alexander. I will not publish what's on the third chart without Alexander's permission, as he hasn't written anything about it here.
Thank you, I can only see that without testing
from you: take a vector, trade
Thanks, I can only see that without testing
Maybe ticks with a certain reading interval will do the trick, but who knows, we'll see Alexander's results.
He checked for the past week, everything was fine, except on the minutes for the week is also good, but on a larger interval UG